Abstract

This paper presents the design of an Ultra-Wide Band (UWB) Low Noise cascaded Amplifier (LNA) used for biomedical applications. The designed structure uses a technique which is based on the inductances minimization to reduce the LNA surface while maintaining low power consumption, low noise and high stability, linearity and gain. To prove its robustness, this technique was studied theoretically, optimized and validated through simulation using the CMOS 0.18 µm process. The LNA achieves a maximum band voltage gain of about 17.5 dB at [1-5] GHz frequency band, a minimum noise figure of 2 dB, IIP3 of + 1dBm and consumes only 13mW under a 2 V power supply. It is distinguished by its prominent figure of merit of 0.68.

Highlights

  • This paper presents the design of an Ultra-Wide Band (UWB) Low Noise cascaded Amplifier (LNA) used for biomedical applications

  • This has become critical for surgically implanted devices where size and battery life are essential as they are implemented in highly sensitive parts of the human body such as eyes for retinal prosthesis and brain for embedded applications n­ eurons[9,10]

  • The low noise amplifier (LNA) has very stringent requirements such as gain, noise, power consumption, inearity and a well-matched input impedance[21]

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Summary

THE CMOS cascaded lna design

The high-power consumption and large area are the two main drawbacks that have limited the cascaded amplifier application space. The resolution of these problems has become a big challenge in order to take full advantage of the intrinsic feature broadband that goes all the way down to consumed current, and the good input and output matching of the amplifier. I­n27, as shown, an example of LNA is designed using several inductances, which increases the amplifier surface. We have minimized the surface area of this architecture by reducing the number of inductances and involving the strategy of the cascaded stages without affecting the other performances.

Inductorless Cell out in
LNA gain analysis
LNA noise analysis
Simulation results
Conclusion
Additional information

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